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DBMS > etcd vs. EXASOL vs. Firebase Realtime Database vs. Fujitsu Enterprise Postgres vs. IRONdb

System Properties Comparison etcd vs. EXASOL vs. Firebase Realtime Database vs. Fujitsu Enterprise Postgres vs. IRONdb

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonEXASOL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed reliable key-value storeHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelKey-value storeRelational DBMSDocument storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.exasol.comfirebase.google.com/­products/­realtime-databasewww.postgresql.fastware.comwww.circonus.com/solutions/time-series-database/
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.exasol.com/­resourcesfirebase.google.com/­docs/­databasewww.postgresql.fastware.com/­product-manualsdocs.circonus.com/irondb/category/getting-started
DeveloperExasolGoogle infoacquired by Google 2014PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyCirconus LLC.
Initial release200020122017
Current release3.4, August 2019Fujitsu Enterprise Postgres 14, January 2022V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoCC and C++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
Windows
Linux
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesyes infotext, numeric, histograms
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoyesnoyesSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsgRPC
JSON over HTTP
.Net
JDBC
ODBC
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Lua
Python
R
Java
JavaScript
Objective-C
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnouser defined functionslimited functionality with using 'rules'user defined functionsyes, in Lua
Triggersyes, watching key changesyesCallbacks are triggered when data changesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Source-replica replicationconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesfine grained access rights according to SQL-standardno
More information provided by the system vendor
etcdEXASOLFirebase Realtime DatabaseFujitsu Enterprise PostgresIRONdb
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
etcdEXASOLFirebase Realtime DatabaseFujitsu Enterprise PostgresIRONdb
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